Automatic speech recognition (“ASR”) technology can be applied to computer based assessments of language proficiency in order to automate scoring, transcription, and feedback generation responsive to oral recitation of an assessment text. Generally, ASR technology suffers from several factors including among other things: low accuracy on non-native spontaneous speech is low; (b) data mismatch between an ASR system during training and during real assessments; and (c) content relevance and context are not widely employed in operational scoring models due to various technological and logistical issues. ASR technology also fails to approach human level scoring of non-native language speakers.